packages <- c("tidyverse", "sf", "readxl", "janitor",
"tidycensus", "viridis", "lubridate",
"ggfx", "albersusa")
if (length(setdiff(packages, rownames(installed.packages()))) > 0) {
install.packages(setdiff(packages, rownames(installed.packages())), repos = "http://cran.us.r-project.org")
}
library(tidyverse)
library(sf)
library(readxl)
library(janitor)
library(tidycensus)
library(viridis)
library(lubridate)
library(ggfx)
library(albersusa)
options(tigris_use_cache = TRUE, tigris_class = "sf")
addUnits <- function(n) {
labels <- ifelse(n < 1000, n, # less than thousands
ifelse(n < 1e6, paste0(round(n/1e3), 'k'), # in thousands
ifelse(n < 1e9, paste0(round(n/1e6), 'M'), # in millions
ifelse(n < 1e12, paste0(round(n/1e9), 'B'), # in billions
ifelse(n < 1e15, paste0(round(n/1e12), 'T'), # in trillions
'too big!'
)))))
return(labels)
}
# Questions ----
# Request this raw data from CSIS
#df2 <- read_excel("../../data/raw_data/CSIS_TNT_Terrorism_US_Jan94-Jan21_Mar2021.xlsx")
df2 <- read_csv("../../data/clean_data/csis_wapo_domestic_terrorism.csv")
df2 <- clean_names(df2)
df2 <- df2 %>%
rename(tnt_orientation=orientation_csis,
year=year_csis,
state=state_csis,
month=month_csis,
vict_killed=vict_killed_csis,
weapon=weapon_csis,
target=target_csis,
lat=lat_csis,
long=long_csis)
# set your census api key
# census_api_key("YOUR API KEY GOES HERE")
county_pov <- get_acs(geography = "county",
variables = "B17001_002",
summary_var = "B17001_001",
geometry = TRUE,
shift_geo = TRUE) %>%
mutate(pctpov = 100 * (estimate/summary_est))
right_spatial <- filter(df2, tnt_orientation=="Violent Far-right") %>%
filter(!is.na(lat)) %>%
st_as_sf(coords=c("long", "lat"), crs = "+proj=longlat") %>%
st_transform(crs=st_crs(county_pov))
right <- st_coordinates(right_spatial$geometry) %>%
data.frame()
colnames(right) <- c("long", "lat")
right_spatial <- cbind(right_spatial, right)
#saveRDS(county_pov, "../../data/clean_data/county_pov.RDS")
#saveRDS(right_spatial, "../../data/clean_data/right_spatial.RDS")
right_spatial_filtered <- right_spatial %>%
filter(year!=1994) %>%
mutate(year_group=case_when(
year >= 1995 & year <2000 ~ "1995-1999",
year >= 2000 & year <2005 ~ "2000-2004",
year >= 2005 & year <2010 ~ "2005-2009",
year >= 2010 & year <2015 ~ "2010-2014s",
year >= 2015 & year <2020 ~ "2015-2019",
year >= 2020 ~ "2020-2021",
)) %>%
count(year_group, lat, long)
us_sf <- usa_sf("laea")
us_sf %>%
ggplot(aes()) +
darklyplot::theme_dark2()+
#geom_sf(aes(fill = pctpov), color=NA) +
geom_sf(fill = "grey", alpha=.8, color="#ffffff") +
with_inner_glow(
geom_sf(fill="black", color = "#ffffff"),
colour = 'red',
sigma = 4
)+
#geom_sf(fill = "white", color=NA) +
with_outer_glow(
with_inner_glow(geom_point(data=right_spatial_filtered,
aes(x=long, y=lat), size=right_spatial_filtered$n*2, color="gold"),
colour="white", sigma=2),
colour="gold", sigma=3,expand=1) +
coord_sf(datum=NA) +
facet_wrap(~year_group, ncol=1) +
labs(title = "Violent Far-right incidents over time",
subtitle = "",
caption = "Source: CSIS",
y="", x="") +
scale_fill_viridis(direction=-1)

2020 and 2021
right_spatial_filtered <- right_spatial_filtered %>%
filter(year_group=="2020-2021")
protests_counties <- read_csv("../../data/clean_data/protests_counties_2020.csv")
county_pov <- left_join(county_pov, protests_counties)
st_list <- protests_counties %>%
filter(!is.na(attendance_racial_just)) %>%
select(GEOID) %>%
pull(GEOID)
paint_map <- function(st="CA",mycolor="red"){
with_inner_glow(geom_sf(fill = "white",
data= .%>% filter(GEOID==st),
color = "#ffffff"),
colour=mycolor,sigma=5)
}
county_pov %>%
ggplot(aes()) +
darklyplot::theme_dark2()+
#geom_sf(aes(fill = pctpov), color=NA) +
geom_sf(fill = NA, alpha=.8, color="#ffffff") +
geom_sf(aes(fill=protests_racial_just)) +
#geom_sf(aes(fill=protests_right_wing)) +
#geom_sf(aes(fill=attendance_racial_just)) +
geom_sf(data=us_sf,fill=NA, color="black") +
#geom_sf(fill = "white", color=NA) +
geom_point(data=right_spatial_filtered,
aes(x=long, y=lat), size=right_spatial_filtered$n*2, color="red") +
coord_sf(datum=NA) +
#facet_wrap(~year_group, ncol=1) +
labs(title = "Violent Far-right incidents in 2020 and 2021",
subtitle = "Compared to number of racial justice protests",
caption = "Source: CSIS, CountLove",
y="", x="") +
scale_fill_viridis(direction=-1)
